Take the suggestion ranking module as an example. A BERT-based ranker is used [1]}. Specifically, it follows the pair prediction formulation (Figure REF  (Middle)). BERT is fine-tuned to score a pair of query \(Q\)  and its candidate suggestion \(S\)  by feeding the concatenation of \(Q\)  and \(S\)  to the model, and predicting the usefulness label \(y \in {1,0}\)  using a logistic regression layer with softmax:
\(P_r(y|Q,S) = \mathrm {softmax}(\mathbf {W} \cdot \mathbf {x}),\) 
